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distilbert-base-uncased-finetuned-artificial
Wiebke/distilbert-base-uncased-finetuned-artificial
distilbert-base-uncased-finetuned-artificial is a text classification model from Wiebke. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- distilbert
- Access
- Public
- Created
- Jan 22, 2024
- Updated
- Jan 24, 2024
- SHA
- 21529254
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Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
distilbert-base-uncased-finetuned-artificial
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- eval_loss: 1.3241
- eval_accuracy: 0.7816
- eval_f1: 0.7801
- eval_runtime: 87.2407
- eval_samples_per_second: 57.313
- eval_steps_per_second: 3.588
- epoch: 1.07
- step: 8000
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Framework versions
- Transformers 4.37.1
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- Created
- Jan 22, 2024
- Updated
- Jan 24, 2024